AI-Augmented Workforce Planning: Leveraging Predictive Analytics for Talent Acquisition and Retention

Authors

  • Anil Chowdary Inaganti  Workday Techno Functional Lead Author
  • Nischal Ravichandran Senior Identity Access Management Engineer Author
  • Sai Rama Krishna Nersu Software Developer Author
  • Rajendra Muppalaneni Lead Software Developer Author

DOI:

https://doi.org/10.69987/

Keywords:

employee retention, predictive analytics, machine learning, workforce optimization, turnover reduction, organizational goals

Abstract

As organizations face increasing pressure to optimize workforce planning in a rapidly changing labor market, AI-augmented workforce planning offers a transformative approach to talent acquisition and retention. This paper explores the integration of artificial intelligence (AI), machine learning (ML), and predictive analytics to enhance workforce strategies. AI-powered systems analyze vast amounts of internal and external data to forecast future workforce needs, identify skill gaps, and predict employee retention risks. By leveraging real-time insights, organizations can proactively address talent shortages, optimize hiring strategies, and create personalized retention programs. This approach helps businesses stay competitive, reduce turnover, and align talent strategies with long-term organizational goals.

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Author Biography

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Published

2021-01-08

Issue

Vol. 2 No. 1 (2021): AI Ethics and Responsible Machine Learning (Jan-Mar'2021)

Section

Articles

License

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

Anil Chowdary Inaganti, Nischal Ravichandran, Sai Rama Krishna Nersu, & Rajendra Muppalaneni. (2021). AI-Augmented Workforce Planning: Leveraging Predictive Analytics for Talent Acquisition and Retention. Artificial Intelligence and Machine Learning Review , 2(1), 10-20. https://doi.org/10.69987/

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